TX 1~AT/TX 2~AT International Journal of Energy Economics and Policy | Vol 11 • Issue 4 • 202124 International Journal of Energy Economics and Policy ISSN 2146 4553 available at http www econjournals[.]
International Journal of Energy Economics and Policy ISSN: 2146-4553 available at http: www.econjournals.com International Journal of Energy Economics and Policy, 2021, 11(4), 24-30 Oil Price and Leverage for Mining Sector Companies in Indonesia Endri Endri1*, M Iqbal Rasyid Supeni1, Yanti Budiasih 2, Matdio Siahaan3, A Razak4, Sudjono Sudjono1 Universitas Mercu Buana, Jakarta, Indonesia, 2Institut Teknologi dan Bisnis Ahmad Dahlan Jakarta, Indonesia, 3Universitas Bhayangkara Jakarta Raya, Indonesia, 4Politeknik Negeri Pontianak, Pontianak, Kalimantan Barat, Indonesia *Email: endri@mercubuana.ac.id Received: 23 February 2021 Accepted: 29 April 2021 DOI: https://doi.org/10.32479/ijeep.11237 ABSTRACT The research was conducted to prove empirically the impact of oil prices, interest rates, profitability, company size, and liquidity on leverage in mining sector companies in Indonesia The study population was 47 companies in the mining sector, using the purposive sampling method, the research sample was selected as many as 32 companies in a period of years from 2014 to 2018 so that 160 observations were obtained The data analysis method used a random-effects model selected from panel data regression The empirical findings show that profitability, liquidity, world oil prices, and interest rates have a negative effect on leverage, while firm size has no impact The empirical findings of this study can help the mining sector industry in Indonesia in making decisions about corporate debt policies that are significantly influenced by oil prices, profitability, liquidity, and interest rates to create optimal debt policies Keywords: Oil Price, Leverage, Mining Sector Companies, Indonesia JEL Classifications: G22, E22, E44, Q43 INTRODUCTION The drop in world oil prices has created high uncertainty for mining companies, which is reflected in their financial performance, particularly concerning the level of debt held by companies Based on data released from the OJK (2019), the total debt of mining sector companies in 2014 amounted to 141.82 trillion rupiahs, experiencing a decrease to 115.62 trillion rupiahs, but in 2018 it experienced a sharp increase of 53% to 137.97 trillion rupiahs The high increase in debt has implications for increasing the company’s financial burden to fulfill its obligations and has the potential to cause financial distress (Endri and Yerianto, 2019) Based on the debt performance of mining sector companies, the average Debt to Total Assets Ratio (DAR) of this sector has decreased since 2015 The DAR average started to increase in 2017 and is consistently increasing until it reached the highest point in the past years in 2018 with 54,01% The lowest DAR average value in this period happened in 2016, with the average value at 50,21% Research on the leverage response to changes in oil prices in mining sector companies has not been widely conducted Many previous studies have proven that changes in stock returns are due to fluctuations in oil prices (Endri et al., 2021; Sivilianto and Endri, 2019; Endri and Nugraha, 2019; Gupta, 2016; Kang et al., 2016; Al-hajj et al., 2018) Aboura and Chevallier (2013) found the opposite effect of leverage due to changes in oil prices Salisu and Fasa (2013) found evidence of the effect of persistence and leverage on oil price volatility Narayan and Nasiri (2020) found that oil market activity affects leverage Domanski et al (2015) reveal that the drop in oil prices has led to a rapid decline in asset value and greater leverage Korotin et al (2017) found the optimal debt portfolio under oil price uncertainty An optimal portfolio can reduce financial risk in the event of oil price uncertainty This Journal is licensed under a Creative Commons Attribution 4.0 International License 24 International Journal of Energy Economics and Policy | Vol 11 • Issue • 2021 Endri, et al.: Oil Price and Leverage for Mining Sector Companies in Indonesia Apart from the price of oil, the company’s leverage is also determined by other factors such as; interest rates, profitability, liquidity, and company size Endri et al (2019), Widyawati and Endri (2018), and Shambor (2017) concluded that an increase in profitability can reduce debt These results differ from studies of Alipour et al (2015) and Saleem et al (2013) which prove that an increase in profitability can increase the company’s leverage Viriya and Suryaningsih (2017) prove that profitability does not affect leverage For company size, Widyawati and Endri (2018), Gómez et al (2016) and Alipour et al (2015) found that a larger company size can reduce leverage, while the findings of Shambor (2017) and Saleem et al (2013) prove otherwise Lumapow (2018) found that firm size is independent of debt policy Research on liquidity was conducted by Shambor (2017), Viriya and Suryaningsih (2017), and Alipour et al (2015) concluded that an increase in liquidity could increase corporate debt, while Sabir and Malik (2012) proved otherwise Mokhova and Zinecker (2014) revealed that in the decisionmaking process regarding the leverage and sources of financing it is also determined by macroeconomic variables The interest rate varies as a macroeconomic variable has an impact on leverage, Dell’Ariccia et al (2014) found that a reduction in interest rates led to greater leverage Bokpin (2009) proved that expectations of an interest rate increase positively influence companies to make changes to debt policy With the phenomenon of a drop in world oil prices and a gap in empirical research, the study identifies the determinants of leverage for mining sector companies in Indonesia, which consist of; oil prices, financial performance, and macroeconomic variables LITERATURE REVIEW Leverage or also known as the capital structure is influenced by three groups of factors, namely; company-specific factors, industry-specific variables, and macroeconomic variables Capital structure theory developed quite rapidly after Modigliani and Miller (1958) first disclosed the proposition of leverage Leverage is an important decision for companies because they have an impact on company value both through the share price channel and the cost of capital (Ahmed and Sabah, 2021) Therefore, in debt policy, companies must be able to create optimal capital structures that maximize share prices or minimize the cost of capital The trade-off theory (TOT) (Jensen and Meckling, 1976) states that the company’s capital structure is achieved through a balance between agency costs and bankruptcy, tax benefits, and others Agency costs can determine the optimal capital structure, so to reduce agency costs, debt structures and ownership must be determined TOT proves that with the tax benefits of large debt and/or bankruptcy costs associated with small debt, profit, size, and growth have a positive impact on leverage Ross (1977) and others developed a leverage theory with information asymmetry between investors and managers, better known as signal theory Ross (1977) and others developed a leverage theory with information asymmetry between investors and managers, which is called the signaling theory Signaling theory says that leverage provides information to investors about cash flow because managers make changes to debt policy to convey profitability and risk to external users The pecking order theory (POT) expressed by Myers (1984) uses a hypothesis of information inequality between shareholders, creditors, and managers when debt or equity is taken POT does not require an optimal capital structure but companies usually follow a sequence of funding options; that is, companies prefer funding from retained earnings to third party funding and prefer debt financing to stock funding The theory of free cash flow (FCFT) was revealed by Jensen (1986) states that companies face a conflict of interest with shareholders and managers by using substantial free cash flow When a company is leveraged, it creates an obligation to pay regular interest This has an impact on decreasing the available cash balance for the company, thereby reducing the incentive for misuse of company cash (Stretcher and Johnson, 2011) Agency costs can be lowered with debt through saving free cash flow and pressuring managers operating at the lowest cost to pay off leverage and avoid bankruptcy 2.1 Profitability and Leverage Profitability is an indicator of the company’s success in generating profits from the production process that is carried out A company with high profit will have a capital overflow, so there is a high chance that the company will have a low level of debt As explained in the POT, it states that “the company with high profitability must have a low level of debt.” The company will prioritize using their internal fundings compared to using external fundings Shahnia et al (2020), Doku et al (2016), Shambor (2017), and Sabir and Malik (2012) concluded that the profitability variable has a negative influence on corporate debt policy The research result of Saleem et al (2013) concluded that the ROE variable has a positive effect on corporate leverage Meanwhile, the research result of Viriya and Suryaningsih (2017) concluded that the ROE variable does not affect corporate debt policy H1: Profitability affects the leverage of mining companies 2.2 Firm Size and Leverage According to the TOT hypothesis, the bigger the company, the higher amount of debt the company can use, which is related to the risks of a big company Low company risk may also cause the cost of debt to be lower than smaller companies, therefore pushing the big companies to borrow bigger in debt Gómez et al (2016) stated that size has a negative effect on company leverage, contrary to the results of Shambor (2017) who found that size has a positive impact on leverage Lumapow’s research (2018) found that the measure is independent of the company’s debt policy H2: Company size affects the leverage of the mining company 2.3 Liquidity and Leverage The liquidity of a company represents an idle balance so that the company can use internal funds as a source of financing POT explains why companies have preference orders in choosing the source of fundings With high liquidity, the company doesn’t need external funding as the internal funding is enough Research is done by Shambor (2017) and Harahap et al (2020) concluded that liquidity has a negative effect on corporate leverage However, a contradictory finding was proposed by Sabir and Malik (2012) International Journal of Energy Economics and Policy | Vol 11 • Issue • 2021 25 Endri, et al.: Oil Price and Leverage for Mining Sector Companies in Indonesia and Endri et al (2020b) that states that liquidity has a positive effect on leverage H3: Liquidity affects the leverage of mining companies 2.4 Oil Price and Leverage The increase in oil prices will increase the chance for mining companies that produce oil to obtain a higher profit On the other hand, for companies in other mining sectors, the increase of world crude oil prices will increase their operational cost, especially on fuel usage The operational cost for fuel has a pretty big portion in the mining industry, therefore if world oil prices increase, companies will find alternative funding, one of which includes increasing debt to fulfill their operational needs This is in line with the POT which explains how companies with large profits have lower leverage Companies with large profits have abundant internal sources of funds Thus, the company will prioritize the use of their internal funding compared to their external funding Research is done by Onguka (2019) and Kelikume and Muritala (2019) state that the world oil price has a negatively significant influence on leverage A contradictory conclusion is made by research done by Wattanatorn and Kanchanapoom (2012), Gupta (2016), and Dadashi et al (2015) which concluded that world oil price has a positive significant influence on corporate debt policy H4: The price of oil affects the leverage of mining companies 2.5 Interest Rate and Leverage Rationally, companies tend to increase debt if interest rates fall because the impact is low-interest expenses Conversely, highinterest rates will have an impact on increasing opportunity costs POT theory states that if there are external funds in the funding of a company, therefore the first alternative of external data chosen is using debts, compared with having to issue new shares If interest rates decline, this will further encourage companies to use debt to meet their funding Conversely, if interest rates increase, this can make companies reconsider using debt because interest costs will be even greater The research was done by Endri et al (2020a), Riaz et al (2014), and Chadegani et al (2011) concluded that the interest rate has a negatively significant impact on corporate debt policy Mokhova and Zinecker (2014) found an opposite relationship between interest rates and capital structure, both long and short term Nejad and Wasiuzzaman (2015) and Memon et al (2015) stated that the company gets more debt if low-interest rates Rehman (2016) found that high interest rates lead to fewer tax benefits than the cost of difficulties arising from the use of debt However, Khémiri and Noubbigh (2018) state that when the interest rate increases, companies tend to increase is followed by the expected increase in inflation Bokpin (2009) found that companies prioritize short-term debt over long-term debt Research conducted by Endri et al (2020), Riaz et al (2014), and Chadegani et al (2011) concluded that an increase in interest rates causes a decrease in corporate leverage Muthama et al (2013) stated that an increase in interest rates can increase long-term debt but has the opposite effect on short-term debt However, the findings of Muthama et al (2013) found that an increase in interest rates increases corporate debt H5: Interest rates affect the leverage of mining companies 26 METHODOLOGY The research population is mining sector companies listed on the Indonesia Stock Exchange from 2014 to 2018 This type of research is causation, which aims to prove hypotheses and analyze the influence between two or more variables on other variables This study aims to estimate the impact of the variable oil price, interest rates, profitability, size, and liquidity on the dependent variable of capital structure The definitions of the research variables and measurements are shown in Table This research uses the data panel, regression model In this model, there are three approaches made up of the random effect model (REM), common effect model (CEM), and fixed-effect model (FEM) The data is processed using the 10th version of EViews software The research model that is estimated is: DARit = α + β1 ROEit + β2 SIZEit + β3 CRit + β4 WTIit + β5 SBIit + εit; Which are : DAR= Debt to Asset Ratio, ROE = Return on Equity, SIZE = Firm Size, CR = Current Ratio, WTI = Oil Price, SBI = BI interest rate, ε = error component, β = slope, α = intercept, N = amount of observation, T = time, N x T = amount of data panel RESULTS AND DISCUSSION 4.1 Statistical Description The result of the statistical data description of the research variables using EViews 10 can be seen in Table 2 ROE variable shows the average of mining companies at −0.013179 with a standard deviation (SD) of 0.857314 This shows that mining companies can generate an operating profit of −1.318% of total equity on average The average value shows that for every rupiah from the shareholder’s equity, there is a loss of 0.1 rupiahs With the average value far from 100%, the company can be said to not yet effectively and efficiently produce a profit The maximum ROE value is 2.181546 from PT Apexindo Pratama Duta Tbk in 2017 while the minimum value is −9.560980 from PT Energi Mega Persada Tbk in 2016 The SIZE variable shows that the average mining company is 16.58927 with a standard deviation of 3.615376 An average value that is greater than the standard deviation indicates that there is no large fluctuation of the SIZE variable in mining companies The highest SIZE score was 22.02344 from PT Indika Energy Tbk in 2018 while the minimum value was 7.889009 from PT Medco Energi Internasional Tbk in 2014 The independent variable of CR shows that the average of mining companies is 1.818922 with a standard deviation of 1.214403 With every rupiah of current liabilities, the company can fulfill the liability 1.8 times from the actual values This condition reflects that the mining company is in good financial health The maximum value of CR is 6.913598 from PT Harum Energy Tbk in 2015 and the minimum value of CR is 0.052391 from PT Astrindo Nusantara Infrastruktur Tbk in 2016 The oil price variable (WTI) shows an average of -0.087360 and an SD of 0.331222 An average value that is smaller than the SD indicates a large fluctuation in the WTI variable During the International Journal of Energy Economics and Policy | Vol 11 • Issue • 2021 Endri, et al.: Oil Price and Leverage for Mining Sector Companies in Indonesia research period, this variable had the highest value of 0.450300 in 2016 and the lowest value of −0.458700 in 2014 The interest rate variable (SBI) shows an average of 0.060500 and an SD of 0.014133 An average value that is greater than the SD indicates that there is no large fluctuation in the SBI variable During the study period, the highest variable value was 0.77500 in 2014 and the lowest value was 0.042500 in 2017 The debt variable (DAR) shows an average of 0.514659 and an SD of 0.226820 The average value means the company has assets that are 51% financed through debt and 49% by equity The highest DAR value was 1.292000 from PT Apexindo Pratama Duta Tbk in 2018 and the lowest DAR value was 0.097800 from PT Harum Energy Tbk in 2015 4.2 Panel Data Regression Model Analysis Panel data regression analysis is applied to identify the factors that influence the company’s debt policy, by selecting one of the models, namely fixed effect, random effect, and common effect The model chosen is based on the paired test using the Hausman test, Chow test, and Lagrange multiplier test Table 1: Variable definition and measurement Var ROE Definition The ability of a company in obtaining profit in conjunction with total equity SIZE Total wealth owned by a company (total asset) CR Company’s ability to fulfill their short term responsibility when due WTI World Oil Price The price used is the crude oil price on sale in West Texas Intermediates (WTI) taken monthly from 2014 to 2018 Calculation units are $/barrel SBI The interest rate used is the SBI interest rate with monthly data from 2014 to 2018 Starting from 19 August 2016, BI 7‑Day Repo Rate is used as a reference interest rate Calculation units are percentage (%) DAR The company’s ability to fulfill its long‑term responsibilities Measurement Profit after ROE = -Tax total Equity SIZE=Ln Total Asset CR = The calculation result showed in Table 3, the chow-test showed that the prob value of the F-test and the chi-square test is equal to 0.0000 < α = 5%, so that H0 is rejected It can be concluded that the FEM is better used to estimate the determinants of firm leverage Table shows the calculation results of the LM-BP test 152.6416 is greater than the chi-square table with α = 0.05 and df = 9, which is 4.321, or the LM-test Breusch-Pagan probability is 0.0000